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Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical Systems from Observation Data

Feng Ding, Jian Pan, Ahmed Alsaedi, Tasawar Hayat
2019 Mathematics  
By using the multi-innovation identification theory, we propose a multi-innovation gradient-based iterative algorithm to improve the performance of the algorithm.  ...  A gradient-based iterative algorithm is derived from observation data by using the gradient search.  ...  multi-innovation gradient-based iterative (MIGI) algorithm.  ... 
doi:10.3390/math7050428 fatcat:aq26ykvbtjformueaa3ccfeaby

Local averaging optimization for chaotic time series prediction

James McNames
2002 Neurocomputing  
This paper describes a new method of optimizing these parameters to minimize the multi-step cross-validation error.  ...  Empirical results indicate that multi-step optimization is susceptible to shallow local minima unless the optimization is limited to ten or fewer steps ahead.  ...  Multi-Step Error Gradient Many of the most efficient optimization algorithms require the gradient of an error function with respect to the model parameters.  ... 
doi:10.1016/s0925-2312(01)00647-6 fatcat:gatur2vjmjfajoxb6ttudodsaq

The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise

Jiling Ding
2017 Complexity  
A gradient based iterative (GI) algorithm and a least squares based iterative (LSI) algorithm are presented for comparison.  ...  This paper considers the identification problem of multi-input-output-error autoregressive systems.  ...  Acknowledgments The author is grateful to her supervisor Professor Feng Ding at the Jiangnan University for his helpful suggestions and the main idea of this work comes from him and his book Multi-Innovation  ... 
doi:10.1155/2017/5292894 fatcat:ly3whserjbam5nnopjsuya7w4q

Iterative Parameter Estimation Algorithms for Dual-Frequency Signal Models

Siyu Liu, Ling Xu, Feng Ding
2017 Algorithms  
The basic idea is to present a gradient-based iterative (GI) algorithm and to estimate the parameters for signal models.  ...  Several estimation errors obtained by the Newton iterative and the moving data window based GI algorithms are compared to the errors given by the GI algorithm.  ...  Using the negative gradient search and minimizing J 1 (θ), introducing an iterative step-size µ k , we can get the gradient-based iterative (GI) algorithm for dual-frequency signal models: θ k =θ k−1 −  ... 
doi:10.3390/a10040118 fatcat:4lmzqyb5sbfuhnxpbt7ztu3mtu

An Improved Method for Stochastic Nonlinear System's Identification Using Fuzzy-Type Output-Error Autoregressive Hammerstein–Wiener Model Based on Gradient Algorithm, Multi-Innovation, and Data Filtering Techniques

Donia Ben Halima Abid, Saif Eddine Abouda, Hanane Medhaffar, Mohamed Chtourou, Carlos Aguilar-Ibanez
2021 Complexity  
Four parametric estimation algorithms to identify the proposed fuzzy-type stochastic output-error autoregressive HW (FSOEAHW) model are derived based on backpropagation algorithm and multi-innovation and  ...  The proposed algorithms are improved backpropagation gradient (IBPG) algorithm, multi-innovation IBPG (MIIBPG) algorithm, a data filtering IBPG (FIBPG) algorithm, and a multi-innovation-based FIBPG (MIFIBPG  ...  At each iteration t and for each sample k, repeat the following steps: Step 2: for input u(k − j), calculate h k− j,t (j � 1, . . . , n b ) using equation (13) .  ... 
doi:10.1155/2021/8525090 fatcat:dpveyjkbejddrimwf76yi3rsbq

Error Corrected References and Acceleration of Norm Optimal iterative Learning Control

David H Owens, Bing Chu
2018 2018 Annual American Control Conference (ACC)  
In this paper a simple mechanism for accelerating the convergence of a well-known Norm Optimal Iterative Learning Control (NOILC) Algorithm is presented by modifying the reference signal each iteration  ...  The change is equivalent to successive application of a gradient and NOILC iteration.  ...  (the step length in normal gradient terminology).  ... 
doi:10.23919/acc.2018.8431404 dblp:conf/amcc/0001C18 fatcat:g5oysxgh75erblhnp7khlugx2u

Verification of a new CFD compressible segregated and multi-phase solver with different flux updates-equations sequences

Raúl Payri, Santiago Ruiz, Jaime Gimeno, Pedro Martí-Aldaraví
2015 Applied Mathematical Modelling  
Verification of a new CFD compressible segregated and multi-phase solver with different flux updates-equations sequences. Applied Mathematical Modelling. 39(2):851-861.  ...  no extra-updates should be used in order to minimize computational cost, but for multi-phase solvers with high density gradients an extra-update should be implemented to improve the stability of the solver  ...  This way, for multi-phase simulations mass fraction and density fields are consistent in every iteration of every time-step.  ... 
doi:10.1016/j.apm.2014.07.011 fatcat:ut7btuwaizh6biaue3pliclhm4

Adaptive pseudospectral solution of a diffuse interface model

Juan J. Tapia, P. Gilberto López
2009 Journal of Computational and Applied Mathematics  
At every step of the continuation process, a fixed number of iterations is implemented, so that the equidistribution equations are not solved completely at each step, which saves a considerable amount  ...  A diffuse interface type model, using an energy-based variational formulation with a free energy that is a function of the density and its gradients is presented.  ...  Conclusions A diffuse interface type model for a multi-phase or multi-component fluid system was derived.  ... 
doi:10.1016/j.cam.2008.04.037 fatcat:z2fb2eruxfavral4xnfernawum

The Study of Fast Optimal Generator Shedding Based on Predictor-Corrector Method

Biao Wang, Zhenghong Wang
2011 Energy Procedia  
large step length, in order to improve computing speed.  ...  This paper presents a fast optimal generator shedding algorithm which is on the basis of predictor-corrector method and time domain simulation for transient stability.  ...  It allows taking emergency control measures for system's stability, when the type II disturbance occurs in the system.  ... 
doi:10.1016/j.egypro.2011.10.049 fatcat:b33r4hmbfvbvnp4gwcqbxdigkq

Research on Traffic Identification Based on Multi Layer Perceptron

Dingding Zhou, Wei Liu, Wengang Zhou, Shi Dong
2014 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
layer perceptron neural network-based method for network traffic identification, and parameters of multi-layer perceptron neural network are analyzed.  ...  years, many machine learning methods have been used in network traffic identification.In order to improve the accuracy and solve some problems of network traffic identification, this paper presents a multi  ...  Acknowledgements This paper is supported by Program for Science and Technology Development of department of science and Technology in Henan Province(102102210265) and Program for Basic and cutting-edge  ... 
doi:10.12928/telkomnika.v12i1.5 fatcat:toeghdnz5vaqpm36lhfe73avci

Research on Traffic Identification Based on Multi Layer Perceptron

Dingding Zhou, Wei Liu, Wengang Zhou, Shi Dong
2014 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
layer perceptron neural network-based method for network traffic identification, and parameters of multi-layer perceptron neural network are analyzed.  ...  years, many machine learning methods have been used in network traffic identification.In order to improve the accuracy and solve some problems of network traffic identification, this paper presents a multi  ...  Acknowledgements This paper is supported by Program for Science and Technology Development of department of science and Technology in Henan Province(102102210265) and Program for Basic and cutting-edge  ... 
doi:10.12928/telkomnika.v12i1.1051 fatcat:e6kihis2yzhnbbt24pe36ma4im

Learning Physical Constraints with Neural Projections [article]

Shuqi Yang, Xingzhe He, Bo Zhu
2020 arXiv   pre-print
We provide a multi-group point representation in conjunction with a configurable network connection mechanism to incorporate prior inputs for processing complex physical systems.  ...  and bending, articulated soft and rigid bodies, and multi-object collisions with complex boundaries.  ...  Acknowledgement We acknowledge the anonymous NeurIPS reviewers for their insightful feedback.  ... 
arXiv:2006.12745v2 fatcat:wsj6xz776ncjpbcqdgth62amca

Optimizing Back-Propagation Gradient for Classification by an Artificial Neural Network

Said El Yamani
2014 American Journal of Physics and Applications  
In this context, this paper proposes to study the parameters that optimize the results of an artificial neural network ANN multilayer perceptron based, for classification of chemical agents on multi-spectral  ...  The mean squared error cost function remains one of the major parameters of the network convergence at its learning phase and a challenge that will face our approach to improve the gradient descent by  ...  the gradient, which operates an iterative approximation along the line of the steepest slope, could be improved by the conjugate gradient algorithm with the search for a minimum which produces a faster  ... 
doi:10.11648/j.ajpa.20140204.11 fatcat:vlp4lejv5bectkz5egzqfbbm6y

Low-Complexity Constrained Recursive Kernel Risk-Sensitive Loss Algorithm

Shunling Xiang, Chunzhe Zhao, Zilin Gao, Dongfang Yan
2022 Symmetry  
Meanwhile, a modified update strategy is developed to avoid the instability of CRKRSL in the early iterations.  ...  Inspired by the smooth kernel risk-sensitive loss (KRSL), a novel constrained recursive KRSL (CRKRSL) algorithm is proposed, which shows higher filtering accuracy and lower computational complexity than  ...  Initialization: Choose step-size µ; kernel width σ; risk-sensitive γ; initial iterative length L; training size N tr ; initial weight w 0 = 0. e n = d n − w T n−1 u n for n = 1 : L w n = Q(w n−1 + µφ(e  ... 
doi:10.3390/sym14050877 fatcat:ifqjqxfv6rbvleria5qc6qj4du

Iterative Least Squares Channel Estimation in Frequency Selective CDMA Systems

A. Rizaner, H. Amca, A.H. Ulusoy, K. Hacioglu
2006 Advanced Int'l Conference on Telecommunications and Int'l Conference on Internet and Web Applications and Services (AICT-ICIW'06)  
Then, we employ an efficient iterative method based on conjugate gradient (CG) algorithm to reduce the computational complexity of the estimation method.  ...  Although, several multi-user channel estimation algorithms have been proposed to mitigate MAI, these algorithms require high computational complexities.  ...  A similar problem for multi-user channel estimation in long-code systems is considered in [1] and a gradient descent (GD) algorithm is suggested for iterative channel estimation.  ... 
doi:10.1109/aict-iciw.2006.120 dblp:conf/aict/RizanerAUHU06 fatcat:qz3modkxy5gfrcmsvwjb7jb42e
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